CLASP (Continuous lifestyle awareness through sweat platform): A novel sensor for simultaneous detection of alcohol and glucose from passive perspired sweat

Abstract

Wearable- IOT based low- cost platforms can enable dynamic lifestyle monitoring through enabling promising and exciting opportunities for wellness and chronic- disease management in personalized environments. Diabetic and pre- diabetic populations can modulate their alcohol intake by tracking their glycemic content continuously to prevent health risks through these platforms. We demonstrate the first technological proof of a combinatorial biosensor for continuous, dynamic monitoring of alcohol and glucose in ultra- low volumes (1– 5μL) of passive perspired sweat towards developing a wearable- IOT based platform. Non-invasive biosensing in sweat is achieved by a unique gold- zinc oxide (ZnO) thin film electrode stack fabricated on a flexible substrate suitable for wearable applications. The active ZnO sensing region is immobilized with enzyme complexes specific for the detection of alcohol and glucose through non- faradaic electrochemical impedance spectroscopy (EIS) and chronoamperometry (CA). Biomolecular interactions occurring at the electrode- sweat interface are represented by the impedance and capacitive current changes in response to charge modulations arising in the double layer. We also report the detection of alcohol concentrations of 0.01– 100 mg/dl and glucose concentrations of 0.01– 50 mg/dl present in synthetic sweat and perspired human sweat. The limit of detection obtained for alcohol and glucose was found to be 0.1 mg/dl in perspired human sweat. Cross- reactivity studies revealed that glucose and alcohol did not show any signal response to cross- reactive molecules. Furthermore, the stable temporal response of the combinatorial biosensor on continuous exposure to passive perspired human sweat spiked with alcohol and glucose over a 120-minute duration was demonstrated.

Integrated omics analysis of sweat reveals an aberrant amino acid metabolism pathway in Vogt–Koyanagi–Harada disease

“…Taking advantage of bioinformatics analysis, our results indicated that amino acid metabolism pathways, shared by the differentially expressed proteins and metabolites, were significantly altered in the VKH group. Although measurement of the sweat chloride concentration (sweat test) is the gold standard for the diagnosis of an immune disorder such as cystic fibrosis (CF) [22] and has also been proposed to monitor glucose in diabetic subjects [23], no other reports have been published so far, to our knowledge, concerning sweat composition in autoimmune disease. Earlier studies have reported the presence of proinflammatory molecules such as cytokines in sweat and showed a good correlation with plasma levels, suggesting that the analysis of sweat might form an alternative method to assess these factors in ambulatory settings where blood collection is difficult [24‐26].…”

A randomized controlled non-inferiority trial of primary care-based facilitated access to an alcohol reduction website (EFAR Spain)

“…Another factor to consider is that, although drop-out reasons have been described, the reasons for patients’ dropout were not clearly registered, which also hinders the interpretation of effectiveness data. Our results suggest that a shift in the implementation direction of digital interventions should be considered, and new approaches to digital interventions should exploit the potential of wearables ( Bhide et al, 2018 ; Dougherty et al, 2014 ; Mohan et al, 2017 ), multiplatform solutions and gamification to increase adherence ( Boyle et al, 2017 ). We hope that our report will improve future studies on digital interventions in this and other settings.…”

Advances in Biosensors for Continuous Glucose Monitoring Towards Wearables

“…This device is not yet wearable, but when tested in real human sweat, it shows great potential in the application towards perspiration-based glucose sensing. This next study takes a non-invasive wearable approach to perspiration-based glucose monitoring ( Bhide et al, 2018 ). It makes use of ultra-low volumes of sweat for rapid and dynamic glucose monitoring, which can be applied to a wearable device in future.…”